Open source AI has been identified as a crucial factor in technological progress, according to a recent announcement. The approach allows for equal access to advanced technology, which fosters competition and innovation that can benefit society and the economy. It is considered essential for maintaining America's leadership in technological advancement, economic growth, and national security.
The focus is on developing robust AI ecosystems amidst a competitive global environment. By balancing risk assessment with innovation, the United States aims to remain competitive and secure the transformative benefits of AI.
A framework has been established to address critical risks related to cybersecurity threats and chemical and biological weapons. This includes identifying potential catastrophic outcomes, conducting threat modeling exercises, and establishing risk thresholds.
"Identifying catastrophic outcomes to prevent: Our framework identifies potential catastrophic outcomes related to cyber, chemical and biological risks that we strive to prevent," states the announcement.
Threat modeling exercises are conducted with external experts when necessary. "These exercises are fundamental to our outcomes-led approach," it was noted.
Risk thresholds are defined based on how models facilitate threat scenarios. Processes are in place to keep these risks within acceptable levels by applying mitigations.
The open-source approach aids in better anticipating and mitigating risk by learning from independent assessments of model capabilities from the broader community. This process improves model efficacy and trustworthiness while contributing to better risk evaluation in the field.
While mitigating severe risks is a primary focus, the technologies being developed also have significant potential societal benefits. Sharing this responsible development approach aims to provide insight into decision-making processes and advance discussions about improving AI evaluation concerning both risks and benefits.
As AI technology evolves, so too will this approach be refined.
